神经网络用于二次优化存在的问题及解决方法

Problems of Neural Networks in Quadratic Optimization and Their Solution

The convergence property of discrete Hopfield neural networks(DHN-N) is studied. It is pointed out that DHN'N is either not convergent or unable to get the global optical solution. A more effidrit algorithm is then proposed, that is suitable for massively paraflel computation since it has the same structure as DHNN. The convergenee of the new algorithm can be guarantee, and an algorithm with high orderof convergence can be derived. Thus, the new algorithm is an effident vary for afl theoptition of quadrahc problems.